Data ethics is an evidence-based approach to understanding the use of data analytics and artificial intelligence (AI) technologies [1]. Hirsch et al.’s Business data ethics reports findings from a 2017 to 2019 empirical study of the motivations and threats for businesses using these technologies. It consists of an introduction, nine core chapters, and a conclusion. Each core chapter contains an abstract, key takeaways, research methodology, and references.

Readers in a hurry to adopt or improve their use of data analytics and AI technologies, or to fix the messes in their current use of them, should start with the conclusion, which summarizes a company case study used for the research; the associated risks of using advanced data analytics and AI (chapter 3); how the company could have gone beyond legal compliance (chapter 4) and the motivations (chapter 5) and policies (chapter 6) to do so; necessary management structures, functions, and processes (chapters 7 and 8); and requisite technical practices (chapter 9).

Business data ethics is a cautionary tale. The concise writing and scholarship bring clarity and confidence. The critical systems thinking is a blueprint for change. Read it now before it is too late.